Space Science and Engineering Center

Abstract. Airborne and ground-based Pandora spectrometer NO2 column measurements were collected during the 2018 Long Island Sound Tropospheric Ozone Study (LISTOS) in the New York City/Long Island Sound region, which coincided with early observations from the Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) instrument. Both airborne- and ground-based measurements are used to evaluate the TROPOMI NO2 Tropospheric Vertical Column (TrVC) product v1.2 in this region, which has high spatial and temporal heterogeneity in NO2. First, airborne and Pandora TrVCs are compared to evaluate the uncertainty of the airborne TrVC and establish the spatial representativeness of the Pandora observations. The 171 coincidences between Pandora and airborne TrVCs are found to be highly correlated (r2= 0.92 and slope of 1.03), with the largest individual differences being associated with high temporal and/or spatial variability. These reference measurements (Pandora and airborne) are complementary with respect to temporal coverage and spatial representativity. Pandora spectrometers can provide continuous long-term measurements but may lack areal representativity when operated in direct-sun mode. Airborne spectrometers are typically only deployed for short periods of time, but their observations are more spatially representative of the satellite measurements with the added capability of retrieving at subpixel resolutions of 250 m × 250 m over the entire TROPOMI pixels they overfly. Thus, airborne data are more correlated with TROPOMI measurements (r2=0.96) than Pandora measurements are with TROPOMI (r2=0.84). The largest outliers between TROPOMI and the reference measurements appear to stem from too spatially coarse a priori surface reflectivity (0.5∘) over bright urban scenes. In this work, this results during cloud-free scenes that, at times, are affected by errors in the TROPOMI cloud pressure retrieval impacting the calculation of tropospheric air mass factors. This factor causes a high bias in TROPOMI TrVCs of 4 %–11 %. Excluding these cloud-impacted points, TROPOMI has an overall low bias of 19 %–33 % during the LISTOS timeframe of June–September 2018. Part of this low bias is caused by coarse a priori profile input from the TM5-MP model; replacing these profiles with those from a 12 km North American Model–Community Multiscale Air Quality (NAMCMAQ) analysis results in a 12 %–14 % increase in the TrVCs. Even with this improvement, the TROPOMI-NAMCMAQ TrVCs have a 7 %–19 % low bias, indicating needed improvement in a priori assumptions in the air mass factor calculation. Future work should explore additional impacts of a priori inputs to further assess the remaining low biases in TROPOMI using these datasets.

Abstract. NASA deployed the GeoTASO airborne UV–visible spectrometer in May–June 2017 to produce high-resolution (approximately 250 m×250 m) gapless NO2 datasets over the western shore of Lake Michigan and over the Los Angeles Basin. The results collected show that the airborne tropospheric vertical column retrievals compare well with ground-based Pandora spectrometer column NO2 observations (r2=0.91 and slope of 1.03). Apparent disagreements between the two measurements can be sensitive to the coincidence criteria and are often associated with large local variability, including rapid temporal changes and spatial heterogeneity that may be observed differently by the sunward-viewing Pandora observations. The gapless mapping strategy executed during the 2017 GeoTASO flights provides data suitable for averaging to coarser areal resolutions to simulate satellite retrievals. As simulated satellite pixel area increases to values typical of TEMPO (Tropospheric Emissions: Monitoring Pollution), TROPOMI (TROPOspheric Monitoring Instrument), and OMI (Ozone Monitoring Instrument), the agreement with Pandora measurements degraded, particularly for the most polluted columns as localized large pollution enhancements observed by Pandora and GeoTASO are spatially averaged with nearby less-polluted locations within the larger area representative of the satellite spatial resolutions (aircraft-to-Pandora slope: TEMPO scale =0.88; TROPOMI scale =0.77; OMI scale =0.57). In these two regions, Pandora and TEMPO or TROPOMI have the potential to compare well at least up to pollution scales of 30×1015 molecules cm−2. Two publicly available OMI tropospheric NO2 retrievals are found to be biased low with respect to these Pandora observations. However, the agreement improves when higher-resolution a priori inputs are used for the tropospheric air mass factor calculation (NASA V3 standard product slope =0.18 and Berkeley High Resolution product slope =0.30). Overall, this work explores best practices for satellite validation strategies with Pandora direct-sun observations by showing the sensitivity to product spatial resolution and demonstrating how the high-spatial-resolution NO2 data retrieved from airborne spectrometers, such as GeoTASO, can be used with high-temporal-resolution ground-based column observations to evaluate the influence of spatial heterogeneity on validation results.

Abstract Satellite remote sensing of precipitable water vapor (PWV) is essential for monitoring moisture in real time for weather applications, as well as tracking the long‐term changes in PWV for climate change trend detection. This study assesses the accuracies of the current satellite observing system, specifically the National Aeronautics and Space Administration (NASA) Atmospheric Infrared Sounder (AIRS) v6 PWV product and the European Organization for the Exploitation of Meteorological Satellite Studies (EUMETSAT) Infrared Atmospheric Sounding Interferometer (IASI) v6 PWV product, using ground‐based SuomiNet Global Positioning System (GPS) network as truth. Elevation‐corrected collocated matchups to each SuomiNet GPS station in North America and around the world were created, and results were broken down by station, ARM region, climate zone, and latitude zone. The greatest difference, exceeding 5%, between IASI and AIRS retrievals occurred in the tropics. Generally, IASI and AIRS fall within a 5% error in the PWV range of 20–40 mm (a mean bias less than 2 mm), with a wet bias for extremely low PWV values (less than 5 mm) and a dry bias for extremely high PWV values (greater than 50 mm). The operational IR satellite products are able to capture the mean PWV but degrade in the extreme dry and wet regimes.

Abstract In our companion study, we show how cloud property products change from MODIS (Moderate Resolution Imaging Spectroradiometer) collection 5.1 (C51) to collection 6 (C6) for both ice and liquid water clouds through a pixel‐to‐pixel comparison. However, the question remains as to the full impacts of these cloud property differences between collections on the inference of cloud radiative effects (CREs). In this study, we address this question from a modeling perspective using one year (2012) of MODIS gridded annual‐averaged ice/liquid water cloud properties at 0.5° × 0.5° spatial resolution. The rapid radiative transfer model for general circulation model applications is used to simulate the broadband radiative fluxes at the top of the atmosphere under clear‐sky and cloudy‐sky conditions. The shortwave, longwave, and net radiative effects of ice, liquid water, and total clouds are derived individually assuming different cloud optical property parameterization schemes. The results provide quantifications of ice and liquid water CRE contributions to the total CRE. We find significant differences in the simulated CREs between C6 and C51 for ice clouds (up to 23 W m −2 for the shortwave CRE) and liquid water clouds (approximately −4.5 W m −2 for the shortwave CRE). The C6 total CRE provides the closest match with the Clouds and the Earth's Radiant Energy System Energy Balanced And Filled product. Sensitivity studies are performed to estimate the impacts of different ice optical parameterization schemes and multilayer cloud overlap assumptions. Results show that the C6–C51 CRE differences are larger than the CRE variations caused by the other factors.

Abstract. Ice clouds are an important element in the radiative balance of the earth's climate system, but their microphysical and optical properties still are not well constrained, especially ice particle habit and the degree of particle surface roughness. In situ observations have revealed common ice particle habits and evidence for surface roughness, but these observations are limited. An alternative is to infer the ice particle shape and surface roughness from satellite observations of polarized reflectivity since they are sensitive to both particle shape and degree of surface roughness. In this study an adding–doubling radiative transfer code is used to simulate polarized reflectivity for nine different ice habits and one habit mixture, along with 17 distinct levels of the surface roughness. A lookup table (LUT) is constructed from the simulation results and used to infer shape and surface roughness from PARASOL satellite polarized reflectivity data over the ocean. Globally, the retrievals yield a compact aggregate of columns as the most commonly retrieved ice habit. Analysis of PARASOL data from the tropics results in slightly more aggregates than in midlatitude or polar regions. Some level of surface roughness is inferred in nearly 70% of PARASOL data, with mean and median roughness near σ = 0.2 and 0.15, respectively. Tropical region analyses have 20% more pixels retrieved with particle surface roughness than in midlatitude or polar regions. The global asymmetry parameter inferred at a wavelength of 0.865 μm has a mean value of 0.77 and a median value of 0.75.

Abstract Passive optical retrievals of cloud liquid water path (LWP), like those implemented for Moderate Resolution Imaging Spectroradiometer (MODIS), rely on cloud vertical profile assumptions to relate optical thickness ( τ ) and effective radius ( r e ) retrievals to LWP. These techniques typically assume that shallow clouds are vertically homogeneous; however, an adiabatic cloud model is plausibly more realistic for shallow marine boundary layer cloud regimes. In this study a satellite retrieval simulator is used to perform MODIS‐like satellite retrievals, which in turn are compared directly to the large‐eddy simulation (LES) output. This satellite simulator creates a framework for rigorous quantification of the impact that vertical profile features have on LWP retrievals, and it accomplishes this while also avoiding sources of bias present in previous observational studies. The cloud vertical profiles from the LES are often more complex than either of the two standard assumptions, and the favored assumption was found to be sensitive to cloud regime (cumuliform/stratiform). Confirming previous studies, drizzle and cloud top entrainment of dry air are identified as physical features that bias LWP retrievals away from adiabatic and toward homogeneous assumptions. The mean bias induced by drizzle‐influenced profiles was shown to be on the order of 5–10 g/m 2 . In contrast, the influence of cloud top entrainment was found to be smaller by about a factor of 2. A theoretical framework is developed to explain variability in LWP retrievals by introducing modifications to the adiabatic r e profile. In addition to analyzing bispectral retrievals, we also compare results with the vertical profile sensitivity of passive polarimetric retrieval techniques.

We present observations of significant dynamics within two UV auroral storms observed on Saturn using the Hubble Space Telescope in April/May 2013. Specifically, we discuss bursts of auroral emission observed at the poleward boundary of a solar wind-induced auroral storm, propagating at ∼330% rigid corotation from near ∼01 h LT toward ∼08 h LT. We suggest that these are indicative of ongoing, bursty reconnection of lobe flux in the magnetotail, providing strong evidence that Saturn's auroral storms are caused by large-scale flux closure. We also discuss the later evolution of a similar storm and show that the emission maps to the trailing region of an energetic neutral atom enhancement. We thus identify the auroral form with the upward field-aligned continuity currents flowing into the associated partial ring current.

Daytime onshore lake breezes are a critical factor controlling ozone abundance at coastal sites around Lake Michigan. Coastal counties along the western shore of Lake Michigan have historically observed high ozone episodes dating to the 1970s. We classified ozone episode days based on the extent or absence of the lake breeze (i.e., "inland", "near-shore" or "no" lake breeze) to establish a climatology of these events. This work demonstrated variable gradients in ozone abundances based on these different types of meteorology, with the sharpest ozone concentration gradients on days with a near-shore lake breeze. On 76-82% of days in which ozone reached 70 ppb for at least 1 hour, a lake breeze was present. Evidence of ozone gradients from multiple observation platforms during the 2017 Lake Michigan Ozone Study (LMOS 2017) are shown for two days with different depths of lake breezes.

Abstract Ship measurements collected over the northeast Pacific along transects between the port of Los Angeles (33.7°N, 118.2°W) and Honolulu (21.3°N, 157.8°W) during May to August 2013 were utilized to investigate the covariability between marine low cloud microphysical and aerosol properties. Ship‐based retrievals of cloud optical depth ( τ ) from a Sun photometer and liquid water path (LWP) from a microwave radiometer were combined to derive cloud droplet number concentration N d and compute a cloud‐aerosol interaction (ACI) metric defined as ACI CCN = ∂ ln( N d )/∂ ln(CCN), with CCN denoting the cloud condensation nuclei concentration measured at 0.4% (CCN 0.4 ) and 0.3% (CCN 0.3 ) supersaturation. Analysis of CCN 0.4 , accumulation mode aerosol concentration ( N a ), and extinction coefficient ( σ ext ) indicates that N a and σ ext can be used as CCN 0.4 proxies for estimating ACI. ACI CCN derived from 10 min averaged N d and CCN 0.4 and CCN 0.3 , and CCN 0.4 regressions using N a and σ ext , produce high ACI CCN : near 1.0, that is, a fractional change in aerosols is associated with an equivalent fractional change in N d . ACI CCN computed in deep boundary layers was small (ACI CCN = 0.60), indicating that surface aerosol measurements inadequately represent the aerosol variability below clouds. Satellite cloud retrievals from MODerate‐resolution Imaging Spectroradiometer and GOES‐15 data were compared against ship‐based retrievals and further analyzed to compute a satellite‐based ACI CCN . Satellite data correlated well with their ship‐based counterparts with linear correlation coefficients equal to or greater than 0.78. Combined satellite N d and ship‐based CCN 0.4 and N a yielded a maximum ACI CCN = 0.88–0.92, a value slightly less than the ship‐based ACI CCN , but still consistent with aircraft‐based studies in the eastern Pacific.

An online-coupled regional Weather Research and Forecasting model with chemistry (WRF-Chem) is utilized incorporating 0.1° × 0.1° spatial resolution HTAP (Hemispheric Transport of Air Pollution) anthropogenic emissions to investigate the spatial and temporal distribution of a Saharan dust outbreak, which contributed to high levels (>50 μg/m3) of daily PM10 concentrations over Turkey in April 2008. Aerosol optical depth and cloud optical thickness retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on board of Aqua satellite are used to better analyze the synoptic conditions that generated the dust outbreak in April 2008. A “Sharav” low pressure system, which transports the dust from Saharan source region over Turkey along the cold front, tends to move faster in WRF-Chem simulations than observed. This causes the predicted dust event to arrive earlier than observed leading to an overestimation of surface PM10 concentrations in WRF-Chem simulation at the beginning of the event.

Abstract We compare differences in ice and liquid water cloud physical and optical properties between Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) collection 6 (C6) and collection 5.1 (C51). The C6 cloud products changed significantly due to improved calibration, improvements based on comparisons with the Cloud‐Aerosol Lidar with Orthogonal Polarization, treatment of subpixel liquid water clouds, introduction of a roughened ice habit for C6 rather than the use of smooth ice particles in C51, and more. The MODIS cloud products form a long‐term data set for analysis, modeling, and various purposes. Thus, it is important to understand the impact of the changes. Two cases are considered for C6 to C51 comparisons. Case 1 considers pixels with valid cloud retrievals in both C6 and C51, while case 2 compares all valid cloud retrievals in each collection. One year (2012) of level‐2 MODIS cloud products are examined, including cloud effective radius (CER), optical thickness (COT), water path, cloud top pressure (CTP), cloud top temperature, and cloud fraction. Large C6–C51 differences are found in the ice CER (regionally, as large as 15 μm) and COT (decrease in annual average by approximately 25%). Liquid water clouds have higher CTP in marine stratocumulus regions in C6 but lower CTP globally (−5 hPa), and there are 66% more valid pixels in C6 (case 2) due to the treatment of pixels with subpixel clouds. Simulated total cloud radiative signatures from C51 and C6 are compared to Clouds and the Earth's Radiant Energy System Energy Balanced And Filled (EBAF) product. The C6 CREs compare more closely with the EBAF than the C51 counterparts.

Abstract Stratosphere‐to‐troposphere transport (STT) and biomass burning (BB) are two important natural sources for tropospheric ozone that can result in elevated ozone and air‐quality episode events. High‐resolution observations of multiple related species are critical for complex ozone source attribution. In this article, we present an analysis of coinciding ground‐based and airborne observations, including ozone lidar, ozonesonde, high spectral resolution lidar (HSRL), and multiple airborne in situ measurements, made on 28 and 29 June 2013 during the Southeast Nexus field campaign. The ozone lidar and HSRL reveal detailed ozone and aerosol structures as well as the temporal evolution associated with a cold front passage. The observations also captured two enhanced (+30 ppbv) ozone layers in the free troposphere (FT), which were determined from this study to be caused by a mixture of BB and stratospheric sources. The mechanism for this STT is tropopause folding associated with a cutoff upper level low‐pressure system according to the analysis of its potential vorticity structure. The depth of the tropopause fold appears to be shallow for this case compared to events observed in other seasons; however, the impact on lower tropospheric ozone was clearly observed. This event suggests that strong STT may occur in the southeast United States during the summer and can potentially impact lower troposphere during these times. Statistical analysis of the airborne observations of trace gases suggests a coincident influence of BB transport in the FT impacting the vertical structure of ozone during this case study.

The three-dimensional global distributions of time-averaged atmospheric heating for January, April, July and October 1979 are estimated from the ECMWF GWE Level IIIb data set. Heating rates are calculated through a vertical integration of the isentropic equation of mass continuity. Estimates of the vertical variation of heating are presented in isobaric coordinates through interpolation of the vertical profiles of heating from isentropic to isobaric coordinates. The horizontal distributions of heating and vertical profiles from various climatological regimes of the planetary circulation provide insight into the four-dimensional structure of the thermal forcing of the atmosphere. The large-scale structure of the heating distributions appears spatially and temporally consistent with known features of the global circulation and the seasonal evolution. Major features of the global distributions include the heating in regions of deep moist convection over South America, equatorial Africa, the ITCZ, the Asian monsoon circulation and the oceanic cyclone tracks of the Northern Hemisphere. The primary centres of heating migrate meridionally and zonally with changing seasons. The meridional migration is linked directly with the annual variation of the latitude of maximum incoming solar radiation. The zonal migration is linked with the planetary scale distribution of continents and oceans and the land-sea surface temperature distribution as determined by the surface energy balance and energy transport within the atmosphere itself. Throughout the tropical-subtropical regions, the strongest heating occurs above 600 mb in association with deep convection. Within the primary centres of heating associated with the Asian monsoon circulation, the maximum heating in the vertical profile is near 400 mb. Over the oceanic storm tracks of the Northern Hemisphere, heating occurs through most of the troposphere. The lower tropospheric heating is maximized in January and in that month is significantly stronger than the heating in the middle troposphere. In July there is negligible heating in the lower troposphere. Profiles from the high latitude continental regions such as central Asia and Canada are in close agreement showing cooling through most of the troposphere in winter and modest heating in summer. Profiles from desert regions over the Sahara and western Australia are also in close agreement showing a transition from low level heating to middle and upper level cooling. Cooling occurs throughout the free troposphere in regions of subtropical anticyclonic circulations over the eastern North and South Pacific Oceans.

Two methods for retrieving cloud droplet effective radius r e from ground‐based near‐infrared spectral measurements of path‐integrated liquid water paths (PLWPs) are described. In one method the PLWP is compared with column measurements of liquid water path (LWP) from a dual channel microwave radiometer (MWR) to estimate the cloud path enhancement, which is then used to derive the cloud droplet effective radius. In the second method, PLWP is combined with absolutely calibrated zenith radiances at 500 nm to retrieve r e and LWP simultaneously. Both techniques are used in a case study of marine stratocumulus at the Barrow, Alaska (71.32°N, 156.62°W) Atmospheric Radiation Measurement Program (ARM) site on 17 September 2004. The first method performed best for moderately thick clouds (LWP ≥ 100 g m −2 ), but the accuracy is limited by uncertainties in the MWR LWP on which it relies. The second method performed well over a wider range of values with 1 σ retrieval errors of <4 g m −2 (∼4%) and ∼3 μ m (∼7%) for 15 ≤ LWP ≤ 170 g m −2 . The LWPs retrieved using the radiance‐PLWP method were highly correlated ( r 2 = 0.96) with LWPs from the MWR (with a bias subtracted) derived using the ARM statistical method. A limited comparison (LWP < 100 g m −2 ) to millimeter wave cloud radar showed that values of r e retrieved using the radiance‐PLWP method were consistently higher (by ∼3 μ m) than the LWC‐weighted mean r e from the radar. Additional field studies are needed to resolve this discrepancy, although this first comparison is promising.

Abstract. Wildfire smoke is one of the most significant concerns of human and environmental health, associated with its substantial impacts on air quality, weather, and climate. However, biomass burning emissions and smoke remain among the largest sources of uncertainties in air quality forecasts. In this study, we evaluate the smoke emissions and plume forecasts from twelve state-of-the-art air quality forecasting systems during the Williams Flats fire in Washington State, the U.S., August 2019, which was intensively observed during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field campaign. Model forecasts with lead times within one day are intercompared under the same framework based on observations from multiple platforms to reveal their performance regarding fire emissions, aerosol optical depth (AOD), surface PM2.5, plume injection, and surface PM2.5 to AOD ratio. The comparison of smoke organic carbon (OC) emissions suggests a large range of daily totals among the models with a factor of 20 to 50. Limited representations of the diurnal patterns and day-to-day variations of emissions highlight the need to incorporate new methodologies to predict the temporal evolution and reduce uncertainty of smoke emission estimates. The evaluation of smoke AOD (sAOD) forecasts suggests overall underpredictions in both the magnitude and smoke plume area for nearly all models, although the high-resolution models have a better representation of the fine-scale structures of smoke plumes. The models driven by FRP-based fire emissions or assimilating satellite AOD data generally outperform the others. Additionally, limitations of the persistence assumption used when predicting smoke emissions are revealed by substantial underpredictions of sAOD on 8 August 2019 mainly over the transported smoke plumes, owing to the underestimated emissions on the 7th. In contrast, the surface smoke PM2.5 (sPM2.5) forecasts show both positive and negative overall biases for these models, with most members presenting more considerable diurnal variations of sPM2.5. Overpredictions of sPM2.5 are found for the models driven by FRP-based emissions during nighttime, suggesting the necessity to improve vertical emission allocation within and above the planetary boundary layer (PBL). Smoke injection heights are further evaluated using the NASA Langley Research Center’s Differential Absorption High Spectral Resolution Lidar (DIAL-HSRL) data collected during the flight observations. As the fire became stronger over 3–8 August, the plume height became deeper with the day-to-day range of about 2–9 km a.g.l. However, narrower ranges are found for all models with a tendency of overpredicting the plume heights for the shallower injection transects and underpredicting for the days showing deeper injections. The misrepresented plume injection heights lead to inaccurate vertical plume allocations along the transects corresponding to transported one-day-old smoke. Discrepancies in model performance for surface PM2.5 and AOD are further suggested by the evaluation of their ratio, which cannot be compensated by solely adjusting the smoke emissions but are more attributable to model representations of plume injections, besides other possible factors including the evolution of PBL depths and aerosol optical property assumptions. By consolidating multiple forecast systems, these results provide strategic insight on pathways to improve smoke forecasts.

Abstract. Global reactive nitrogen emissions into the air have increased to unprecedented levels. Limiting the loss of reactive nitrogen into the environment is one of the major challenges for humankind. At the current levels ammonia (NH3) is a threat to both the environment and human health. However, relatively little is known about the total nitrogen budget and distribution around the world, due in part to the sparseness of observations over most of the globe. Recent advances in the capabilities of measuring NH3 with satellite instruments have improved the situation with sensors such as the Infrared Atmospheric Sounding Interferometer (IASI) and the Cross-Track Infrared Sounder (CrIS) making twice daily observations with global coverage. However, these require validation to be truly useful, and one of the main challenges in the validation of the satellite NH3 profile and total column data products is the scarcity of measurements that can be directly compared. Presented here is the validation of the CrIS Fast Physical Retrieval (CFPR) NH3 column and profile measurements using ground-based Fourier Transform Infrared (FTIR) observations. We use the total columns and profiles from seven FTIR sites in the Network for the Detection of Atmospheric Composition Change (NDACC) to validate the satellite data products. The overall FTIR and CrIS total columns compare well with a correlation of r = 0.77 (N= 218) with very little bias (a slope of 1.02). Binning the comparisons by total column amounts, for concentrations larger than 1.0 x 1016 molecules cm−2, i.e. ranging from moderate to polluted conditions, the relative difference is on average ~ 0–5 % with a standard deviation of 25–50 %, which is comparable to the estimated retrieval uncertainties in both CrIS and the FTIR. For the smallest total column range where there are a large number of observations at or near the CrIS noise level (detection limit) and the FTIR total columns are smaller than 1.0 x 1016 molecules cm−2, the absolute differences between CrIS and the FTIR total columns are small with CrIS showing a slight positive column bias around +2.4 x 1015 (standard deviation = 5.5 x 1015) molecules cm−2, which corresponds to a relative difference of ~ +50 % (std = 100 %). The CrIS retrievals for these comparisons typically show good vertical sensitivity down to ~850 hPa, and at this level the retrieved profiles also compare well with the median absolute difference of 0.87 (±0.08) ppb and a corresponding median relative difference of 39 (±2) %. Most of the absolute and relative profile comparison differences are in the range of the estimated retrieval uncertainties. However, the CrIS retrieval does tend to overestimate the concentrations in the levels near the surface at low concentrations, most probably due to the detection limit of the instrument, and at higher concentrations shows more of an underestimation of the concentrations in these lower levels.

<p>The interest in the possibility of life on Venus is driven not just by curiosity about life originating in another Earth-like environment, but because of the possibility that life may be playing a critical role in the planet’s present, and possibly its past, atmospheric state. The brilliance of Venus in the night sky (as viewed from Earth) is due to its highly reflective cloud cover, about 28 km thick at the equator.  Its spectral albedo is about 90% at wavelengths > 500 nm, but it drops gradually to about 40% around 370 nm before rising slightly at shorter wavelengths.  This albedo drop is due to the presence of several absorbers in the atmosphere and the cloud cover.  A very large fraction of the energy absorbed by Venus is at ultraviolet wavelengths with sulfur dioxide above the clouds contributing to the absorption below 330 nm; however, the identities of the other absorbers remain unknown.  The inability to identify the absorbers that are responsible for determining the radiative energy balance of Venus over the last century is a major impediment to understanding how the planet “works”, a major component of NASA’s efforts in planetary exploration.  Limaye et al. (Astrobiology <strong>18</strong>, 1181-1198, 2018) presented a hypothesis suggesting that cloud-based microbial life could be contributors to the spectral signatures of Venus’ clouds, building upon previous suggestions of the possibility of life in the clouds of Venus.</p><p>Four interconnected themes for the exploration of Venus as an astrobiology target are: – (i) investigations focused on the likelihood that liquid water existed on the surface in the past leading to the potential for the origin and evolution of life, (ii) investigations into the potential for habitable zones within Venus’ clouds and Venus-like atmospheres, (iii) theoretical investigations into how active aerobiology may impact the radiative energy balance of Venus’ clouds and Venus-like atmospheres, and (iv) application of these investigative themes towards better understanding the atmospheric dynamics and habitability of exoplanets. These themes can serve as a basis for proposed Venus Astrobiology Objectives and suggestions for measurements for future missions, as per the goals and objectives developed by the Venus Exploration Analysis Group (VEXAG), which is sponsored by NASA to plan for the future exploration of Venus.  </p><p>A Venus Collection to be published in Astrobiology journal in 2021 will include papers from the  “Habitability of the Venus Cloud Layer”, Moscow (October 2019) workshop. </p>

Current operational weather satellites from the United States provide high temporal (GOES), spatial, spectral, and radiometric resolution data and derived products for fire detection and monitoring. These include GOES-16/17 for geostationary missions and Suomi NPP and NOAA-20 for low earth orbiting satellites. The Advanced Baseline Imager (ABI) on the latest geostationary satellites provide 16 channels, including a dedicated fire detection channel along with near-infrared channels which can aid with fire detection at night [1], [2].